First, what CLS is about

• Computational Literary Studies
• Aimed at analyzing (large amounts of) textual data…
• … by computational techniques

Leon Battista Alberti

Leon Battista Alberti, De componendis cifris, ca. 1466

Computation into criticism

John Burrows, Computation into Criticism, 1987

Distant reading

Franco Moretti, Matt Jockers, Ted Underwood

Sociology of reading

Karina van Dalen-Oskam, Het raadsel literatuur, 2021

Quantitative linguistics

Foundations of CLS

• Computation into criticism
• Distant reading
• Stylometry
• Authorship attribution
• Digital humanities
• Language resources
• Digital libraries
• Natural language processing
• Machine learning
• Big data
• …

What CLS has to offer

• Scientific method
  • reproducibility, empirical paradigm, statistical modeling, probabilistic inference, …
• Scale
  • access to unprecedented amounts of data
• Accuracy ability to capture patterns invisible to a naked eye

Blase Pascal and two infinities

Combination of factors needed

• Datasets (language resources)
• Tools (computer programs)
• Suitable methodology
• Computer power (i.e. scientific instruments)

Libraries, journals, publishers, …

Dictionaries at IJP PAN

ELTeC corpus

DraCor

infrastructures in DH and CLS

• in hard sciences, infrastructures are tangible
  • servers, telescopes, accelerators, …
• in the humanities, institutions are essential
  • libraries, publishing houses, journals, …
• in DH, multifaceted needs
  • the notion of infrastructure needs reconsideration
  • corpora (FAIR!) but not only

CLS INFRA project

• text collections (corpora)
  • quality
  • metadata
  • conversion
• methodology
  • tools (NLP, datavis, …)
  • tool chains
  • methodological considerations
  • bibliographic survey
• network of scholars
  • training schools
  • short-term research stays
  • collaboration with COST Action

Overarching idea is to connect…

• People
  • To establish a network of CLS researchers
• Data
  • To consolidate existing high-quality corpora…
  • …covering prose, drama and poetry
• Tools
  • To build a chain of NLP tools to analyze texts
• Methods
  • To provide a survey of state-of-the-art methods

The project’s structure

The team (30+ people)

Julie Birkholz, Ingo Börner, Joanna Byszuk, Sally Chambers, Vera Maria Charvat, Silvie Cinková, Tess Dejaeghere, Julia Dudar, Matej Ďurčo, Maciej Eder, Jennifer Edmond, Evgeniia Fileva, Frank Fischer, Serge Heiden, Michal Křen, Bartłomiej Kunda, Michał Mrugalski, Ciara Murphy, Carolin Odebrecht, Marco Raciti, Salvador Ros, Christof Schöch, Artjoms Šeļa, Toma Tasovac, Justin Tonra, Erzsébet Tóth-Czifra, Peer Trilcke, Karina van Dalen-Oskam, Lisanne van Rossum

training schools

• Prague 2022
  • NLP tools
  • 25 participants on site
  • many more remotely
• Madrid 2023
  • text analysis
  • tentative dates: 10-11 May
• Vienna 2024
  • corpus queries
  • tentative dates: spring 2024

TNA

• transnational access
• short-term research stays…
• in one of 6 institutions:
  • NUI Galway
  • Uni Potsdam
  • Uni Trier
  • UNED Madrid
  • OEAW Vienna
  • Charles Uni, Prague
• everyone eligible
• two calls every year

deliverables published

• 3.1 Report on the methodological baseline for (computational) literary studies
• 4.1 Report on the skills matrix for computational literary studies
• 5.1 Review of the data landscape
• 6.1 Assembly of existing data